collaborators

7 papers

cs.CV2026

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation

Zian Li, Litong Gong, Borui Liao +6

Diffusion models have enabled high-quality video generation in recent years, but the high cost of iterative sampling hinders their practical deployment. Few-step distillation allev…

cs.LG2026

Toward Better Geometric Representations for Molecule Generative Models

Shaoheng Yan, Zian Li, Cai Zhou +3

Geometric representation-conditioned molecule generation provides an effective paradigm that decouples molecule representation modeling from structure generation. By decoupling mol…

cs.LG2026

MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference

Ruijie Zhou, Fanxu Meng, Yufei Xu +4

DeepSeek Sparse Attention (DSA) sets the state of the art for fine-grained inference-time sparse attention by introducing a learned token-wise indexer that scores every prefix toke…

cs.LG2026

FlashMol: High-Quality Molecule Generation in as Few as Four Steps

Xinyuan Wei, Zian Li, Shaoheng Yan +2

Generating chemically valid 3D molecular conformations is critical for computational drug discovery. Classical diffusion-based models like GeoLDM perform well but require hundreds…

cs.LG2026

Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation

Cai Zhou, Zijie Chen, Zian Li +7

Many generative tasks in chemistry and science involve distributions invariant to group symmetries (e.g., permutation and rotation). A common strategy enforces invariance and equiv…

cs.CV2025

CanvasMAR: Improving Masked Autoregressive Video Prediction With Canvas

Zian Li, Muhan Zhang

Masked autoregressive models (MAR) have emerged as a powerful paradigm for image and video generation, combining the flexibility of masked modeling with the expressiveness of conti…

cs.LG2025

GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining

Shaoheng Yan, Zian Li, Muhan Zhang

The pretraining-finetuning paradigm has powered major advances in domains such as natural language processing and computer vision, with representative examples including masked lan…